Machine logic: Even with flaws, programs that weed out applicants can be good gatekeepers

By Marco Buscaglia and Tribune Content Agency

CareerBuilder|

Nov 25, 2018 | 9:20 AM

The days of recruiters sifting through hundreds of hard-copy resumes by hand or scanning through their online counterparts on computer screens are long gone. And that's to job seeker's benefit, especially if you're an active applicant who networks and uses contacts to find new positions. (Lightpoet/Dreamstime.com)

You know those friends who can't score a job interview? The ones who tell you they're being unfairly dumped by the candidate-sifting programs used to separate the qualified from the unqualified?

"I never had a chance," he'll tell you.

"The system's rigged," she'll say.

Maybe. Or maybe Friend No. 1 isn't mindful of the words he's using on his resume, especially as it applies to a specific job. Never mind that an ad he responded to stressed how the sales department worked on a flat-salary model; your offended friend decided to include the words "commission" and "bonus" 22 times in his online application, not exactly the terms the candidate-seeking program wants to read.

Word choice may have affected Friend No. 2. It's possible that one of the awards she listed in her application raised a giant red flag. After all, most automated programs wouldn't recognize "2017 Killer Beast" as the name of her current company's employee of the year award. Instead, a candidate-selecting program might have read it as a job skill or worse, a personality description.

No going back

"I understand that people think applicant programs can miss certain candidates but I think it happens a lot less often than people think. But it's a fair complaint. Really, though, what are the alternatives? How far do people want to go back?" asks -- let's just call her HR Mary -- a veteran human resources specialist who says she's been "hiring and firing people" for 29 years. HR Mary says she'd rather be "anonymous and honest than identifiable and vague," hence the cloak-and-dagger moniker.

The days of recruiters sifting through hundreds of hard-copy resumes by hand or scanning through their online counterparts on computer screens are long gone. "That's to the job seeker's benefit, especially if you're an active applicant who networks and uses contacts to find new positions," HR Mary says. "A face in the crowd is a face in the crowd, whether it's a hard-copy face or a digital face. People don't realize the vast amounts of applicants for jobs, especially good jobs. I was once responsible for choosing 10 candidates out of a pool of 412 resumes. I'd be lying if I told you I even made it past 200 before choosing 10. And trust me, my approach was the norm, not the exception."

Unbiased approach

While old-school job seekers may lament the candidate-choosing programs that now serve as corporate gatekeepers, HR Mary says there is an obvious, if not admitted, benefit. "We've removed the bias. It's not built into the algorithms," she says. "If you have to get past a recruiter who strongly dislikes a certain college or has a bias against a certain company, you may be the best candidate in the world but you may never get the interview. The program doesn't care about any of that. If you're qualified, you move on."

It goes beyond schools and companies, HR Mary admits. "I've suspected certain people in the industry of having unwritten rules about who does and doesn't get an interview," she says. "You can figure that one out. Maybe it's a bias against women or a certain race or nationality but it's possible. But a computer program doesn't care. It reads skills and experience, not gender and race."

Proceeding with caution

Not all HR professionals place their trust entirely in algorithms and other standard forms of program-based decisions, especially if they feel they've already had experience with a candidate who they feel shouldn't have made it past the first round of cuts. A study by Berkeley J. Dietvorst, Joseph Simmons and Cade Massey from the University of Pennsylvania found that people distrust algorithms and decision-making programs once they experience questionable results. When humans make similar misjudgments, people are much more forgiving. "Research shows that evidence-based algorithms more accurately predict the future than do human forecasters. Yet, when forecasters are deciding whether to use a human forecaster or a statistical algorithm, they often choose the human forecaster," wrote Dietvorst in an article about the study for the American Psychological Association.

"People I've worked with say they're 'going with their gut' when they want to bypass decisions made by a computer program, like their gut has a better set of criteria than a program that's been created with very a specific set of requirements," says HR Mary. "Granted, there are some people that we just have strong feelings about, that we want to push toward the finish line because they're original. A lot of times, eccentric candidates with unique backgrounds get stuck in our mind and we want to help them. But most times, our gut-feeling is wrong. There's a reason they didn't make it past the initial candidate pool but we're so committed to the idea of making this incredible hire, we ignore the obvious. It's almost impossible for us to admit that we were wrong and the program was right."